This work focuses the recognition of complex human activities in video data. A combination of new features and techniques from speech recognition is used to realize a recognition of action units and their combinations in video sequences. The presented approach shows how motion information gained from video data can be used to interpret the underlying structural information of actions and how higher level models allow an abstraction of different motion categories beyond simple classification.

This two-volume set LNCS 12131 and LNCS 12132 constitutes the refereed proceedings of the 17th International Conference on Image Analysis and Recognition, ICIAR 2020, held in Póvoa de Varzim, Portugal, in June 2020. The 54 full papers presented together with 15 short papers were carefully reviewed and selected from 123 submissions. The papers are organized in the following topical sections: image processing and analysis; video analysis; computer vision; 3D computer vision; machine learning; medical image and analysis; analysis of histopathology images; diagnosis and screening of ophthalmic diseases; and grand challenge on automatic lung cancer patient management. Due to the corona pandemic, ICIAR 2020 was held virtually only.

A synergy of techniques on hybrid intelligence for real-life image analysis Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding. As such, the focus is on the methods of computational intelligence, with an emphasis on hybrid intelligent methods applied to image analysis and understanding. The book offers a diverse range of hybrid intelligence techniques under the umbrellas of image thresholding, image segmentation, image analysis and video analysis. Key features: Provides in-depth analysis of hybrid intelligent paradigms. Divided into self-contained chapters. Provides ample case studies, illustrations and photographs of real-life examples to illustrate findings and applications of different hybrid intelligent paradigms. Offers new solutions to recent problems in computer science, specifically in the application of hybrid intelligent techniques for image analysis and understanding, using well-known contemporary algorithms. The book is essential reading for lecturers, researchers and graduate students in electrical engineering and computer science.

The book provides insights into the Second International Conference on Computer Vision & Image Processing (CVIP-2017) organized by Department of Computer Science and Engineering of Indian Institute of Technology Roorkee. The book presents technological progress and research outcomes in the area of image processing and computer vision. The topics covered in this book are image/video processing and analysis; image/video formation and display; image/video filtering, restoration, enhancement and super-resolution; image/video coding and transmission; image/video storage, retrieval and authentication; image/video quality; transform-based and multi-resolution image/video analysis; biological and perceptual models for image/video processing; machine learning in image/video analysis; probability and uncertainty handling for image/video processing; motion and tracking; segmentation and recognition; shape, structure and stereo.

Continuous improvements in technological applications have allowed more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but it increases the overall probability of technological progression. The Handbook of Research on Machine Learning Innovations and Trends is a key resource on the latest advances and research regarding the vast range of advanced systems and applications involved in machine intelligence. Highlighting multidisciplinary studies on decision theory, intelligent search, and multi-agent systems, this publication is an ideal reference source for professionals and researchers working in the field of machine learning and its applications.

Proceedings of the 3rd International Conference on Multimedia Technology (ICMT2013) focuses on both the theory and applications of multimedia technology. The recent advances, new research findings and applications in the fields of theoretical, experimental and applied image & video processing and multimedia technology presented at the conference are brought together in this book. It will serve as a valuable reference for scientists and engineers working in multimedia and related fields. Prof. Aly A. Farag works at the University of Louisville, USA; Prof. Jian Yang works at Tsinghua University, China; Dr. Feng Jiao works at Nanjing University of Information Science & Technology, China.

This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition.

Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field.The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security. - Very relevant to current research challenges faced in various fields - Self-contained reference to machine learning - Emphasis on applications-oriented techniques

Humans are social beings that interact with others in their surroundings. In a public space, for example on a train platform, one can observe the wide array of social actions humans express in their daily lives. There are for instance people hugging each other, waving to one another or shaking hands. A large part of our social behavior consists of carrying out such social actions and the recognition of those actions facilitates our interactions with other people. Therefore, action recognition has become more and more popular as a research topic over the years. Actions do not only appear at our point of fixation but also in the peripheral visual field. The current Ph.D. thesis aims at understanding action recognition in the human central and peripheral vision. To this end, action recognition processes have been investigated under more naturalistic conditions than has been done so far. This thesis extends the knowledge about action recognition processes into more realistic scenarios and the far visual periphery. In four studies, life size action stimuli were used (I) to examine the action categorization abilities of central and peripheral vision, (II) to investigate the viewpoint-dependency of peripheral action representations, (III) to behaviorally measure the perceptive field sizes of action sensitive channels and (IV) to investigate the influence of additional actors in the visual scene on action recognition processes. The main results of the different studies can be summarized as follows. In Study I a high categorization performance for social actions throughout the visual field with a nonlinear performance decline towards the visual periphery was shown. Study II revealed a viewpoint-dependence of action recognition only in far visual periphery. In Study III large perceptive fields for action recognition were measured that decrease in size towards the periphery. And in Study IV no influence of a surrounding crowd of people on the recognition of actions in central vision and the visual periphery was shown. In sum, this thesis provides evidence that the abilities of peripheral vision have been underestimated and that peripheral vision might play a more important role in daily life than merely triggering gaze saccades to events in our environment.

This unique text/reference provides a coherent and comprehensive overview of all aspects of video analysis of humans. Broad in coverage and accessible in style, the text presents original perspectives collected from preeminent researchers gathered from across the world. In addition to presenting state-of-the-art research, the book reviews the historical origins of the different existing methods, and predicts future trends and challenges. Features: with a Foreword by Professor Larry Davis; contains contributions from an international selection of leading authorities in the field; includes an extensive glossary; discusses the problems associated with detecting and tracking people through camera networks; examines topics related to determining the time-varying 3D pose of a person from video; investigates the representation and recognition of human and vehicular actions; reviews the most important applications of activity recognition, from biometrics and surveillance, to sports and driver assistance.